Vu Dinh

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Lam Si Tung HoAssociate Professor, Department of Mathematics and Statistics, Dalhousie UniversityVerified email at dal.ca
Frederick "Erick" A. Matsen IVProfessor, Fred Hutchinson Cancer Research CenterVerified email at fredhutch.org
Gregery T BuzzardProfessor of Mathematics, Purdue UniversityVerified email at purdue.edu
Cuong V. NguyenDurham UniversityVerified email at durham.ac.uk
Ann RundellAssociate Professor of Biomedical Engineering, Purdue UniversityVerified email at purdue.edu
Binh NguyenAssociate Professor, University of Science, Vietnam.Verified email at hcmus.edu.vn
cheng zhangPeking UniversityVerified email at pku.edu.cn
Ankush ChakrabartyPrincipal Research Scientist at Mitsubishi Electric Research Laboratories (MERL)Verified email at merl.com
Stanislaw H. ŻakProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
Duy NguyenPh.D. Statistics, University of Wisconsin-MadisonVerified email at stat.wisc.edu
Aaron DarlingIllumina Australia; Professor @ University of Technology SydneyVerified email at illumina.com
Connor McCoyFred Hutchinson Cancer Research CenterVerified email at fhcrc.org
Mathieu FourmentUniversity of Technology SydneyVerified email at uts.edu.au
Martin CorlessAeronautics & Astronautics, Purdue UniversityVerified email at purdue.edu
Arman BilgeComputational evolutionary biologistVerified email at armanbilge.com
Bradley J. LucierProfessor Emeritus of Mathematics and Computer Science, Purdue UniversityVerified email at math.purdue.edu
Dor Ben-AmotzPurdue UniversityVerified email at purdue.edu
Marc A. SuchardProfessor, University of California, Los AngelesVerified email at ucla.edu
Huan XuAlibaba IncVerified email at alibaba-inc.com
Jeffrey P PerleyPurdue UniversityVerified email at purdue.edu

Vu Dinh

University of Delaware

Verified email at udel.edu - Homepage

Phylogenetics Machine learning Uncertainty quantification


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Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences A Chakrabarty, V Dinh, M Corless, AE Rundell, SH Zak, GT Buzzard IEEE, 2016	84	2016
Mel-frequency cepstral coefficients for eye movement identification NV Cuong, V Dinh, LST Ho 2012 ieee 24th international conference on tools with artificial …, 2012	66	2012
Probabilistic path hamiltonian monte carlo V Dinh, A Bilge, C Zhang, FA Matsen IV International Conference on Machine Learning, 1009-1018, 2017	56	2017
Consistent feature selection for analytic deep neural networks VC Dinh, LS Ho Advances in Neural Information Processing Systems 33, 2420-2431, 2020	45	2020
Effective online Bayesian phylogenetics via sequential Monte Carlo with guided proposals M Fourment, BC Claywell, V Dinh, C McCoy, FA Matsen IV, AE Darling Systematic biology 67 (3), 490-502, 2018	36	2018
Binary complementary filters for compressive Raman spectroscopy OG Rehrauer, VC Dinh, BR Mankani, GT Buzzard, BJ Lucier, ... Applied spectroscopy 72 (1), 69-78, 2018	33	2018
Online Bayesian phylogenetic inference: theoretical foundations via sequential Monte Carlo V Dinh, AE Darling, FA Matsen IV Systematic biology 67 (3), 503-517, 2018	31	2018
Robust explicit nonlinear model predictive control with integral sliding mode A Chakrabarty, V Dinh, GT Buzzard, SH Żak, AE Rundell 2014 American Control Conference, 2851-2856, 2014	22	2014
Proceedings of the 34th International Conference on Machine Learning. Proceedings of Machine Learning Research V Dinh, A Bilge, C Zhang, FA Matsen	20	2017
Learning from non-iid data: Fast rates for the one-vs-all multiclass plug-in classifiers V Dinh, LST Ho, NV Cuong, D Nguyen, BT Nguyen Theory and Applications of Models of Computation: 12th Annual Conference …, 2015	18	2015
Fast learning rates with heavy-tailed losses VC Dinh, LS Ho, B Nguyen, D Nguyen Advances in neural information processing systems 29, 2016	16	2016
Generalization and robustness of batched weighted average algorithm with V-geometrically ergodic Markov data NV Cuong, LST Ho, V Dinh Algorithmic Learning Theory: 24th International Conference, ALT 2013 …, 2013	12	2013
Consistent feature selection for neural networks via Adaptive Group Lasso V Dinh, LST Ho arXiv preprint arXiv:2006.00334, 2020	11	2020
Experimental design for dynamics identification of cellular processes V Dinh, AE Rundell, GT Buzzard Bulletin of mathematical biology 76, 597-626, 2014	10	2014
Multi-task learning improves ancestral state reconstruction LST Ho, V Dinh, CV Nguyen Theoretical Population Biology 126, 33-39, 2019	8	2019
Consistency and convergence rate of phylogenetic inference via regularization V Dinh, LST Ho, MA Suchard, FA Matsen IV Annals of statistics 46 (4), 1481, 2018	7	2018
The shape of the one-dimensional phylogenetic likelihood function V Dinh, FA Matsen IV The annals of applied probability: an official journal of the Institute of …, 2017	7	2017
A machine learning approach to identifying important features for achieving step thresholds in individuals with chronic stroke AE Miller, E Russell, DS Reisman, HE Kim, V Dinh Plos one 17 (6), e0270105, 2022	6	2022
Searching for minimal optimal neural networks LST Ho, V Dinh Statistics & Probability Letters 183, 109353, 2022	6	2022
Bayesian active learning with abstention feedbacks CV Nguyen, LST Ho, H Xu, V Dinh, BT Nguyen Neurocomputing 471, 242-250, 2022	6	2022

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